ppxscal/embedding_network huggingface dataset:
How satisfactory is it to communicate customer knowledge with the aid of multimodal interaction metaphors?
Authors: Mutlaq B. Alotaibi, Dimitrios I. Rigas
Venue: Proceedings of the 8th WSEAS International Conference on Software engineering, parallel and distributed systems (2009)

The purpose of this paper was to examine the implications of employing multimodal interaction metaphors in Electronic Customer Knowledge Management Systems (E-CKMS). There are several challenges to E-CKMS, such as trust and knowledge retention, structured transfer of knowledge and information overload. As empirical investigations that examine the impact of multimodal interaction on customer satisfaction are generally lacking, this paper describes an experimental study conducted to evaluate this role and measure user satisfaction. This evaluation was carried out empirically by implementing an E-CKMS experimental platform with two interfaces (text with graphics and avatar-enhanced). Two independent groups of users (n=20 for each group) evaluated the two interface conditions in terms of five user satisfaction factors. Results suggested that user satisfaction was significantly improved by incorporating audio-visual metaphors.
Towards Semi-supervised Manifold Learning: UKR with Structural Hints
Authors: Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Helge Ritter
Venue: Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps (2009)

We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-supervised way. These new extensions are targeted at representing a dextrous manipulation task. We thus evaluate the effectiveness of the proposed mechanisms on appropriate toy data that mimic the characteristics of the aimed manipulation task and thereby provide means for a systematic evaluation.
Statistically Based Process Monitoring: Lessons from the Trench
Authors: Maria Teresa Baldassarre, Nicola Boffoli, Giovanni Bruno, Danilo Caivano
Venue: Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes (2009)

Monitoring software processes is a non trivial task. Recently many authors have suggested the use of Statistical Process Control (SPC) for monitoring software processes, while others have pointed out its potential pitfalls. Indeed, the main problem is that SPC is often used "as is" without the appropriate customizations or extensions needed for making it applicable to software contexts. This work points out and discusses four main issues related to software process monitoring and highlights how SPC can be used as solution to address each problem. The solutions arise from experience collected by the authors during empirical investigations in industrial contexts. As so, this work is intended as a first step in clarifying how SPC can contribute to practically solve some monitoring issues and guide practitioners towards a more disciplined and correct use of the approach in controlling software processes.
Combining fault injection and model checking to verify fault tolerance in multi-agent systems
Authors: Jonathan Ezekiel, Alessio Lomuscio
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

The ability to guarantee that a system will continue to operate correctly under degraded conditions is key to the success of adopting multi-agent systems (MAS) as a paradigm for designing complex agent based fault tolerant systems. In order to provide such a guarantee, practically usable tools and techniques for verifying fault tolerant MAS architectures are urgently required. In this paper we address this requirement by combining automatic fault injection with model checking to verify fault tolerance in MAS. We present a generic method to mutate a model of a correctly behaving system into a faulty one, and show how the mutated model can be used to reason about fault tolerance, which includes recovery from faults. The usefulness of the proposed method is demonstrated by injecting automatically a fault into a sender-receiver protocol, and verifying temporal and epistemic specifications of the protocol's fault tolerance using the MCMAS model checker.
AHT Bézier curves and NUAHT B-spline curves
Authors: Gang Xu, Guo-Zhao Wang
Venue: Journal of Computer Science and Technology (2007)

In this paper, we present two new unified mathematics models of conics and polynomial curves, called algebraic hyperbolic trigonometric (AHT) Bézier curves and non-uniform algebraic hyperbolic trigonometric (NUAHT) B-spline curves of order n, which are generated over the space span{sin t, cos t, sinh t, cosh t, 1, t,..., tn-5}, n ≥ 5. The two kinds of curves share most of the properties as those of the Bézier curves and B-spline curves in polynomial space. In particular, they can represent exactly some remarkable transcendental curves such as the helix, the cycloid and the catenary. The subdivision formulae of these new kinds of curves are also given. The generations of the tensor product surfaces are straightforward. Using the new mathematics models, we present the control mesh representations of two classes of minimal surfaces.
Incremental maintenance of length normalized indexes for approximate string matching
Authors: Marios Hadjieleftheriou, Nick Koudas, Divesh Srivastava
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Approximate string matching is a problem that has received a lot of attention recently. Existing work on information retrieval has concentrated on a variety of similarity measures TF/IDF, BM25, HMM, etc.) specifically tailored for document retrieval purposes. As new applications that depend on retrieving short strings are becoming popular(e.g., local search engines like YellowPages.com, Yahoo!Local, and Google Maps) new indexing methods are needed, tailored for short strings. For that purpose, a number of indexing techniques and related algorithms have been proposed based on length normalized similarity measures. A common denominator of indexes for length normalized measures is that maintaining the underlying structures in the presence of incremental updates is inefficient, mainly due to data dependent, precomputed weights associated with each distinct token and string. Incorporating updates usually is accomplished by rebuilding the indexes at regular time intervals. In this paper we present a framework that advocates lazy update propagation with the following key feature: Efficient, incremental updates that immediately reflect the new data in the indexes in a way that gives strict guarantees on the quality of subsequent query answers. More specifically, our techniques guarantee against false negatives and limit the number of false positives produced. We implement a fully working prototype and illustrate that the proposed ideas work really well in practice for real datasets.
Reference Point Detection for Arch Type Fingerprints
Authors: H. K. Lam, Z. Hou, W. Y. Yau, T. P. Chen, J. Li, K. Y. Sim
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Reference point detection is an important task in the design of an automated fingerprint identification system. Many algorithms have emerged with acceptable results but are mostly suitable for non-arch type fingerprint. It still remains as a challenging problem to reliably identify reference points for fingerprints of the arch type. A topological method is presented in this paper to detect reference points in arch type fingerprint images. To evaluate the performance, 400 arch type fingerprint image pairs in the NIST DB4 database are utilized. The alignment accuracy on average is about 35 pixels in distance and 9 degrees in orientation, which is very well comparable with respect to state-of-the-arts as designed for non-arch type fingerprints.
Risk preparedness and management scheme for military units
Authors: Nikolaos V. Karadimas, Nikolaos Doukas, Nikolaos P. Papastamatiou
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

This work comes to propose the application of Job Rotation model in risk preparedness and management for military units. It describes the design of an innovative training and employment scheme based on the Job Rotation model customized around risk preparedness and management for the army. The proposed model initially addresses the systematic training of selected military officers in risk prevention and crisis management. This initial group of military officers will depart for military units substituting units' officers that will be selected to follow the same risk management training. The initial group of military officers while being allocated to units will implement an initial risk, and associated contingency plan with the support of risk management experts (their trainers and mentors). When the rotation will end, the military officers of the units that participated to the rotations will return to their positions with duty to update, disseminate, and realize the plans in case of hazardous situations.
Parallel MLEM on Multicore Architectures
Authors: Tilman Küstner, Josef Weidendorfer, Jasmine Schirmer, Tobias Klug, Carsten Trinitis, Sybille Ziegler
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

The efficient use of multicore architectures for sparse matrix-vector multiplication (SpMV) is currently an open challenge. One algorithm which makes use of SpMV is the maximum likelihood expectation maximization (MLEM) algorithm. When using MLEM for positron emission tomography (PET) image reconstruction, one requires a particularly large matrix. We present a new storage scheme for this type of matrix which cuts the memory requirements by half, compared to the widely-used compressed sparse row format. For parallelization we combine the two partitioning techniques recursive bisection and striping. Our results show good load balancing and cache behavior. We also give speedup measurements on various modern multicore systems. 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
An effective convergence independent loop closure method using Forward-Backward Cyclic Coordinate Descent
Authors: Kamal Al-Nasr, Jing He
Venue: International Journal of Data Mining and Bioinformatics (2009)

Cyclic Coordinate Descent (CCD) is a popular robotic approach to generate a possible loop that closes the gap between two constrained portions of a protein chain (Canutescu and Dunbrack 2003). In this paper, we describe an effective Forward-Backward CCD (FBCCD) method to connect the two constrained portions of a protein chain without requiring the loop to converge. A test of 30 loops of length 4, 8 and 12 suggests that our method takes fewer number of cycles to produce loops of comparable accuracy and more accurate second portion of the chain, when it is compared to the CCD method.
Classification with Unknown Classes
Authors: Chetan Gupta, Song Wang, Umeshwar Dayal, Abhay Mehta
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

Given a data set D, such that (X i ,y i ) ¿ D, y i ¿ ¿, we are interested in first dividing the range of y i , i.e. (y max ¿ y min ), (where y max is the maximum of all y i corresponding to (X i ,y i ) ¿ D and y min is the minimum of all y i corresponding to (X i ,y i ) ¿ D), into contiguous ranges which can be thought of as classes and then for a new point, X j , predicting which range (class) it falls into. The problem is difficult, because neither the size of each range nor the number of ranges, is known a-priori.This was a practical problem that arose when we wanted to predict the execution time of a query in a database. For our purposes, an accurate prediction was not required, while a time range was sufficient and the time ranges were unknown a-priori.To solve this problem we introduce a binary tree structure called Class Discovery Tree. We have used this technique successfully for predicting the execution times of a query and this is slated for incorporation into a commercial, enterprise level Database Management System.In this paper, we discuss our solution and validate it on two more real life data sets. In the first one, we compare our result with a naive approach and in the second, with the published results. In both cases, our approach is superior.
WebNC: efficient sharing of web applications
Authors: Laurent Denoue, John Adcock, Scott Carter, Gene Golovchinsky
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

WebNC is a system for efficiently sharing, retrieving and viewing web applications. Unlike existing screencasting and screensharing tools, WebNC is optimized to work with web pages where a lot of scrolling happens. WebNC uses a tile-based encoding to capture, transmit and deliver web applications, and relies only on dynamic HTML and JavaScript. The resulting webcasts require very little bandwidth and are viewable on any modern web browser including Firefox and Internet Explorer as well as browsers on the iPhone and Android platforms.
Information Sharing and Interaction in Collaborative Convergence
Authors: Daniel Suthers, Ravi Vatrapu, Richard Medina, Nathan Dwyer
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

In multiple research literatures, successful collaborative problem solving and learning is analyzed in terms of success of information sharing. In this paper we report analyses of an experimental study that bring the sufficiency of an information sharing account of collaboration into question. One treatment group achieved greater convergence and integration of information in their handling of a complex problem, yet this same group shared less information in a hidden profile design. An additional analysis was conducted to assess whether interaction beyond information sharing accounts for the convergence and integration. The pattern of convergence is more closely mirrored by interactivity quantified as the number of “round trips” addressing the same information items.
Multiuser radio resource allocation for multiservice transmission in OFDMA-based cooperative relay networks
Authors: Xing Zhang, Shuping Chen, Wenbo Wang
Venue: EURASIP Journal on Wireless Communications and Networking (2009)

The problem of multiservice transmission in OFDMA-based cooperative relay networks is studied comprehensively. We propose a framework to adaptively allocate power, subcarriers, and data rate in OFDMA system to maximize spectral efficiency under the constraints of satisfying multiuser multiservices' QoS requirements. Specifically, first we concentrate on the single-user scenario which considers multiservice transmission in point-to-point cooperative relay network. Based on the analysis of single-user scenario, we extend the multiservice transmission to multiuser point-to-multipoint scenario. Next, based on the framework, we propose several suboptimal radio resource allocation algorithms for multiservice transmissions in OFDMA-based cooperative relay networks to further reduce the computational complexity. Simulation results show that the proposed algorithms yield much higher spectral efficiency and much lower outage probability, which are flexible and efficient for the OFDMA-based cooperative relay system.
Third-party composition of aop mechanisms
Authors: David H. Lorenz
Venue:  (2008)

Domain-specific aspect-oriented language extensions offer unique capabilities to deal with a variety of crosscutting concerns. In principle, one should be able to use several of these extensions together in a single program. In practice, however, each extension implements its own specialized weaver and the different weavers are incompatible. Even if the weavers were compatible, combining them is a difficult problem in general, because each extension defines a new language with its own semantics. In this dissertation work, we introduce, analyze and present a solution to the aspect extension composition problem. We present a scalable, general, and practical framework, named AWESOME, for composing aspect weavers. To be scalable, the AWESOME framework supports third-party composition of aspect weavers. To be general, the framework provides means for customizing the composition behavior. Furthermore, to be practically useful, there is no framework-associated degradation in the performance of compiled aspect programs.
Extraction of the Reduced Training Set Based on Rough Set in SVMs
Authors: Hongbing Liu, Shengwu Xiong, Qiong Chen
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

In SVMs, the data points lying in the interactive regions of two classes are very important to form the hyperplane and difficult to be classified. How to select the reduced training set only including the interactive data points is one of the important issues. There are many methods by which the easy misclassified training data are selected to speed up training. The extraction method of the reduced training set is proposed by using the boundary of rough set. Firstly, for two-class problem, the entire training set is partitioned into three regions: the region only containing the positive samples, the region only composed of the negative samples and the boundary region including not only the positive samples but also the negative ones. Secondly, the boundary region is the intersection of two classes and selected to train SVMs. Thirdly, the two-class and multi-class problems are used to verify the feasibility of the proposed SVMs. The experimental results on the classic benchmark data set of machine learning show that the proposed learning machines can downsize the number of training data and hardly influence on their generalization abilities.
Adaptive encryption for the realization of real-time transmission of sensitive medical video streams
Authors: Kai Kamphenkel, Markus Blank, Jens Bauer, Georg Carle
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

This paper presents an analysis of the potential of adaptive encryption of streaming video data over 3G networks. The results obtained promote the design of a network component (the so called “intelligent network”) that facilitates the secure real-time transmission of video data. Case studies involving the sensitive area of telemedicine can be implemented by means of this component. The transport layer protocol SCTP is the basis for technical realization, which has interesting features and extensions. The combination of these features and the management of the intelligent network allows the implementation of sensitive applications.
Multiagent dynamic reasoning about belief and trust
Authors: Daniel G. Schwartz
Venue:  (2008)

In this dissertation we design a system that allows Semantic Web agents to reason within what has come to be known as the Web of Trust. We integrated reasoning about belief and trust, so agents can reason about information from different sources and deal with contradictions. Software agents interact to support users who publish, share and search for documents in a distributed repository. Each agent maintains an individualized topic taxonomy for the user it represents, updating it with information obtained from other agents. Additionally, an agent maintains and updates trust relationships with other agents. When new information leads to a contradiction, the agent performs a belief revision process informed by a degree of belief in a statement and a degree of trust an agent has for the information source. The system described has several key characteristics. First, we define a formal language with well-defined semantics within which an agent can express the relevant conditions of belief and trust, and a set of inference rules. The language uses symbolic labels for belief and trust intervals to facilitate expressing inexact statements about subjective epistemic states. Second, an agent&rsquo;s belief set at a given point in time is modeled using a Dynamic Reasoning System (DRS). This allows the agent&rsquo;s knowledge acquisition and belief revision processes to be expressed as activities that take place in time. Third, we explicitly describe reasoning processes, creating algorithms for acquiring new information and for belief revision. Fourth, we design a general architecture for system implementation. An object-oriented model presents classes and methods implementing the formal model. The database model is flexible and allows for future extensions. Finally, an external representation for system data is presented based on open Semantic Web standards.
WISE: Automated test generation for worst-case complexity
Authors: Jacob Burnim, Sudeep Juvekar, Koushik Sen
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Program analysis and automated test generation have primarily been used to find correctness bugs. We present complexity testing, a novel automated test generation technique to find performance bugs. Our complexity testing algorithm, which we call WISE (Worst-case Inputs from Symbolic Execution), operates on a program accepting inputs of arbitrary size. For each input size, WISE attempts to construct an input which exhibits the worst-case computational complexity of the program. WISE uses exhaustive test generation for small input sizes and generalizes the result of executing the program on those inputs into an “input generator.” The generator is subsequently used to efficiently generate worst-case inputs for larger input sizes. We have performed experiments to demonstrate the utility of our approach on a set of standard data structures and algorithms. Our results show that WISE can effectively generate worstcase inputs for several of these benchmarks.
Detecting the Learner's Motivational States in An Interactive Learning Environment
Authors: Lei Qu, W. Lewis Johnson
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

It is important for pedagogical agents to have the ability to detect the learner's motivational states. With this ability, agents will be more sensitive to the cognitive and emotional states of the learner and be able to promote the learner's motivation through interaction with the learner. In this paper we present a method for agents to assess learner's motivational states in an interactive learning environment. It takes into account the learner's attention, current task and expected time to perform the task. An experiment was conducted to collect data for evaluating the performance of the method, and the results showed that there is more than 75% to detect the learner's motivational states where intervention is warranted.